The Story of Data
with Laura Warren, Principal Storylytics
The data usually doesn't speak for itself. Depending on the audience, the need, and the problem data can have a lot of things to say to different people. Laura Warren of Storylytics shares today how she helps businesses use data analysis to tell the right story to decision-makers in a business situation.
Notes from the Show
Storylytics is a firm that teaches the skill of telling stories with data that will resonate with decision-makers in or for a business. Today Principal of Storylytics, Laura Warren, joins me to discuss the importance of data storytelling.
The biggest mistake consults and businesses often make is assuming the data will speak for itself. Consultants often think that everyone will see the data and information the way they see it, but this is typically not the case. For Storylytics, Audience Centric storytelling is very important. The data story is developed based on the audience and the possible action they can take.
Laura identifies three “truths” that help determine the perspective of the decision-making audience:
Business Truth - The what and why an individual thinks the problem is.
Personal Truth - A personal and unique bias to the problem or data based on experience or views.
Influencer Truth - The power an individual has to take the information and make change.
When telling the story of data, the how is going to differ which each audience, problem, and other key details. Laura laid out the format for how a data story should look:
Problem and Hypothesis - What is the problem and what does the audience already think?
Observation - What has been observed about this problem?
Implication - Teaser of the solution.
Analysis - The data details, numbers, and analysis.
Conclusion - The solution and needed action.
Laura and her team have a great “formula” and framework when it comes to every step of data storytelling. You can look forward to more education in the future from Storylytics when it comes to data storytelling for smaller businesses and solopreneurs. To get in contact with Laura Warren, connect with her on LinkedIn, via email, or check out the Storylytics website.
What is Data Storytelling?
The framework for presenting a data story.
How to create an audience-centric data story.
Mistakes consultants make working & communicating with data.
Mentioned in this Episode:
Transcribed by AI Susan Tatum 00:38
Welcome back, everybody. Today, my guest is Laura Warren, who's the principal at storylitics. And this is going to be a great conversation today because Laura's specialty is working with people who influence decision makers or influence others through the use of data. And how to best do that. And I know that I have been guilty many times making the data should speak for itself. And it doesn't really work. From a persuasion point of view, persuasion and influence can be words that are used for evil, but we're using them for good here and Laura I'm so happy to have you with us today. So welcome.
Laura Warren 01:21
Thank you. I'm so happy to be here.
Susan Tatum 01:23
Tell tell us a little bit, just give us like the one two minute deal on who you are and what you do.
Laura Warren 01:29
Okay, well, I am leading storylitics founded storylitics about seven, eight years ago. And the reason why I've formed story Linux was because as a career researcher, or career data person, I was finding I was having more and more conversations with senior leaders, despite the fact that we were actually getting better and better data, because of big data and how it's easier to collect and everything like that. It was having more and more conversations, it said, I just need to know what it means. And what that really meant was that I'm getting all this data, I'm getting all this information, but I actually don't have the ability of understanding how do I now use it. And because I was having so many conversations with leaders about that, it was a matter of you know, the power of the information is in your hands, not mine, I can come in with you on an ad hoc basis, to tell you what this information means for you. But the strength of being able to do that is you and your people being able to translate that on a regular basis. And that is a skill, not a talent. So storylitics was found to actually start teaching people the skill of telling stories with data that are really going to resonate with decision makers. So that's what I do today.
Susan Tatum 02:36
Okay, so what is it that? What are the mistakes that experts or consultants or whomever? What are the mistakes that we're making with data?
Laura Warren 02:46
You know, I think you said it best right in the very beginning of that intro there is that we can always feel guilty that the data is going to speak for itself, that it often is, because we are so close to the information, we look at it and go, it's right there. It's fantastic. And we put it out there with that assumption that people are going to make that connection between here's what the data says. But here's the risk that it means for us or the opportunity that it's highlighting, we assume they make that link. And that is not often the case. And the reason why they're not making that link is because that's why they've actually called us is to help them make that link and then be able to understand what we want to do with it. So because I think it's the biggest mistake that we make is that we assume that the data will speak for itself, we assume our audience members will see exactly what we see with the information. And then we get confused when people don't buy into what the recommendation is. And the reason they're not buying into the recommendation is because they don't understand the link that had to happen before it. So that's the biggest thing is we assume what we see is exactly what everybody else is going to see. And we fail to make that connection back to the decision makers.
Susan Tatum 03:49
So let me give a a really simple example from my life. Okay, from my from my business life, so So I know I help fill pipelines. And I know from looking, I'm looking at data and I'm seeing this, this, this form of outreach is going to get a result and a 30% response acceptance rate, this outreach is going to result in a 50% acceptance rate, this outreach may be it take a little bit more work. But the data is showing that you're going to get a better result. So in this case, I might just show I could have just showed a slide that says This one's getting 30%, this one's getting 50% and then assume that they understand that that's what we should do. I realize this is a really simple result.
Laura Warren 04:47
No, it's yeah, it's meaningful, because you added something in there. So this one might take a little bit more work, but it's going to result in the 50%.
Susan Tatum 04:57
Laura Warren 04:57
right. And that I think that's the important piece, I think, yeah, I recognize this is simple, but I think there's something very important in there that you're capturing 30%, 50% I want 50% Let's go with a 50% recommendation, right? And then the issue is, is it'll be more 50%. But I need four more of your people. I need you to be doing this type of work in order to get us to the 50% that little bit of extra time that goes into it.
Susan Tatum 05:22
Laura Warren 05:22
Is that piece where we get all excited about what the results could be. But the process element that we need to buy into to make sure that that will actually happen is what again, we can sometimes get caught in not actually explaining which impacts the execution it impacts the result? It impacts how how well do we think the consultant actually did for us if they actually didn't say that part? So I didn't get 50%. So why didn't I get 50%? Well, because of this, this and this, we forgot to say those parts.
Susan Tatum 05:50
It seems like so Okay, so do you lead with the data? And then, and then talk about the the reason the the recommendations based on the data? Or do you lead with the recommendation? Here's, here's what, here's what we think you should do. And oh, here's why we think you should do that.
Laura Warren 06:10
Yeah, so let's just take a step back, because it always depends. And I hate that phrase, but it really does. So it always depends on who it is that you're talking to. So I talk a lot about something called Audience centric data storytelling. So if we stick with this 30 50% example that you're talking about, to just as a starting point with that, when we say 30% 50%, we want to be able to say, well, who is it that we're actually talking to? And as a result of that 30 50% example, if I'm talking to this person, what action can that person take as a result of that? So as an example, if you're speaking to the Social Media Manager, the one who's going to be responsible for some doing that outreach, there might be some things that you need to talk about within there versus you were talking to the finance person that actually wants to be able to say, what do I need to do financially to support a 30 50%? so the that and because that has an impact on how do you actually lead.
Susan Tatum 07:10
I can, yeah. And then so part of your teaching, is that is that teaching folks to understand their audience to start to start with your audience? That makes perfect sense. What, what are you having them do to how to how do they start with the audience?
Laura Warren 07:29
So the audience entropy is mean, it's always we've got this great phrase, it says, understand your audience. But there's so many things that we do there. When we're talking about data storytelling, there's three things that I talk that your audience really wants from you when it comes to data, right? So it's like, help me solve my problems but tell me how I can be part of it? And how is it going to help me? Like, what am I going to do? So give me an answer, engagement as part of it, and then tell me what I need to do.
Susan Tatum 08:09
Laura Warren 08:10
involve me in the conversation into sort of, don't just dictate to me, and therefore you must do, I want to understand it. I want to know what role I play in it. And then I want to know what I actually need to do. That's what your audience really wants when you're actually talking about data. So in order for you to deliver on that, so first of all, we need to understand that's what your audience wants. Yeah, the way that you actually figure out how you deliver on that is right up front. When we say well, how do you be audience centric? Well, let's understand what the actual question is. So I want to be able to do this. Well, why is that I want to do this, I want to figure out what my problem is here so that I can do this instead. So back to that simple answer. I want to be able to figure out how I can improve my Forgive me, what were the 30 50%? Should have done?
Susan Tatum 08:40
Well, let's just say it was a positive response to, let's say, having a conversation.
Laura Warren 08:50
So on an outreach discussion,
Susan Tatum 08:51
Laura Warren 08:54
Yeah. Okay. So I want to be able to make sure that I have a, I want to be able to optimize my outreach discussion so that I can have a positive response, which is going to lead to greater sales.
Susan Tatum 09:04
Laura Warren 09:05
right. So the end of the day, we actually know all of this is really about, I can tell you how to have a positive outreach discussion, but a positive outreach discussion is actually defined on getting a positive sales rate. So the question is not really about have a great discussion. The question is about how do you actually drive increase your sales from the point of from that first point of engagement,
Susan Tatum 09:25
Laura Warren 09:26
So it's, that's so that this was a little bit more difficult to target a sales situation. But in the data situation, it's the exact same thing. I want to be able to figure out why this is going on, so that I can do something differently. So that way, we actually know what we're really trying to solve for here. I'm not trying to give you a 50% number, I'm trying to tell you, this is going to help you get to x,
Susan Tatum 09:44
your ultimate goal,
Laura Warren 09:45
your ultimate goal. And when it comes to data, I mean, it's one of these things, it's so it's easy and intuitive when we talk about it from a data perspective, from a pardon me from a sales perspective, like if we're trying to actually engage with something we always want to be able to understand what our client's "Why" is right. Always. whenever we're going into talk to them, saying, Well, what do you like, what are we really trying to sell What are you really trying to accomplish? We always do that when we're doing sales. We do not always do when we're talking about the data, because the data is just a number. But when we actually are trying to be able to do analytics, that so that we can element becomes important. And a lot of people forget it. Even seasoned analysts can forget it to actually do that this so that we can but it's not just that. That's just one piece of it. That's just the mechanics of getting to the right thing. When you're dealing with data when you get in to that persuasion influence piece. The other piece that we really wanted to be able to talk about is what are they already think? So what do they already think is going on? What do they already know about what's going on with the data? So I have this problem that I know I need to be able to look at the data. And what do they think is actually the driver, what's really on their mind. Because once we actually understand what's really on their mind, that's how we can actually provide an insight. Because this is kind of the other thing that I think a lot of people forget, or the one of the biggest not forget, but one of the biggest mistakes that we make, is that we assume what's insightful to us is insightful to the audience members. But that's not always the case. Because we actually define what an insight is an Insight means that I am telling you something that you did not already know that it's beneficial to the problem at hand. But the big thing is, is like what do you already know? Because what's really insightful for me could be completely old hat to you. Well, of course, that's what's going on. Or what I assume is self evident, is like earth shatteringly disruptive to them, like what's, but without actually knowing what they already are aware of today, you don't actually know where the insights are, because they define the insight, not you.
Susan Tatum 11:46
So let me I think I may have distracted us a little bit with my own example trying to find out which is, so give us one that's maybe a bit more data centric, an example that you would run into.
Laura Warren 11:59
So an example that I often talk about is one with a client that I had actually done that was dealing with was meat. So my apologies for any non meat eaters that might be listening to this. But it was about it was about meat. And where the client was actually a meat producer. And the question that had come from their VP of Marketing had been the came to the people that I was working with, had been Can you guys let me know exactly how our sales are doing in Western Canada. By retailer... can totally do that for you very easy, you know that you get that dopamine hit, I can totally run that for you, I can get it back to you in five minutes. All is good in the world. But that wasn't really what the question was when they actually started a probe beyond like, Well, why are you asking me? What are you already thinking? What do you want to do with it? The question became, there's something very simple that went from, hey, I need to understand how our sales are doing in Western Canada. But the reason why I need to understand what our sales are doing in Western Canada is because we're having a problem with one of our retailers who's promoting one of our competitors, right against us at a price point that we can't hit. But we haven't changed any of our supply chain stuff. So once I figure out exactly if that's really the problem with what's going on in Western Canada, I need to go and talk to our supply chain, folks, because our spoilage is really high. And we need to do some better planning. So the question was not about sales rate. The question was about spoilage. And what they really wanted to be able to understand was, how do we actually now need to manage our supply chain, while we get this promotional situation under control?
Susan Tatum 13:30
So the that means digging into when when say a client comes to you, or if it's internal, whoever you're trying to get this answer for, presents it, here's what I want to know. You're saying it's very important to understand why they want to know that
Laura Warren 13:47
it's critical and understand why they want to know that, and also what's on their mind. So that whole piece in terms of being able to say, well, we can't hit that price point. Therefore, I think that we're actually losing sales when we're on promotion. And I need to figure out how we're going to manage our supply chain against that becomes really, really important when you actually get to the point where you're bringing the information back, which is the storytelling piece. So yes, we need to probe right up front, so that we understand what it is. But where that gets really impactful is when we want to go back and tell the story.
Susan Tatum 14:22
So let's keep on with this, the row that you're going down here about how does that become the story.
Laura Warren 13:26
So the way in which we tell a story is by being able to say is to really talk about with the what the data is or observations, explain what it means to them, and risk and opportunity, and then what we can do about it. And you ask the question before about do you lead with the recommendation? Or do you lead with the data? I always say, I'm here to be able to help you understand what's going on with supply chain, because it'll be interesting to discover that we have some opportunities to actually increase our production based on what we found. So I lead with, here's a problem here to solve for a little bit of a teaser as to where we're going the answer because then you get let's tell me more engagement in terms of I've given you a little bit of an answer. But let me tell you more about what's going on. And then let me bring you to the to the full conclusion so we can figure out what we want to do. So you get you do lead a little bit with the answer. So I'm here to tell you, like answer this question for you. And this is what the answer is going to be a little bit but let me tell you like let me tell you how we got there. I know that we were thinking to start with here's what you were theorizing. I know that you were concerned about what was happening when we were on promotion, and that there was a drop within our overall sales volume. When we took a look at it what was actually very interesting to See, till we start with Well, what did you think, was very interesting to see that we were not actually seeing a drop within our promotion, like when they were on sale, we weren't actually seeing a drop within our promoted activity during those particular weeks. So what you thought was happening is not happening. So you start by actually, with data storytelling, you start by addressing what do you already think? Prove It, validate or invalidate it? So we have a hypothesis. Was that true or not true? Where do we go from there? So here's what we first learned, which tells us that was not actually what's going on. But here's what we did find. And then that's what the information is, but always make the link. So I'm gonna tell you what it is. Here's what we observed, which tells us this. So observation implication. So observation is here's what it told us. But what implication actually means is, what does this now mean for us now that we found this, let me make sure that I'm connecting the dots by telling you what risk opportunity or changing perspective this is actually brought to you. So it's not just the data, I need to tell you actually articulate for you risk opportunity change in perspective, this is what this data has given us. So in this particular situation, giving you a perspective. So we thought that that was actually going on. But what we really found was that were promotions were actually the same, we weren't really seeing it. So changing perspective, drove a little bit deeper, what is actually going on, when we have a competitor going in here, what we're actually finding is that because of this new price point, what's really happening is we're getting new consumers actually coming into the category. So because we've got this new price point, people are actually getting a little bit more, it's drawing more attention to this category. That's not exactly an exciting category. And what that's actually meant is that we're getting increased foot traffic. So our promotions are doing just fine. It's a regular sales volumes that are having a problem. And what that really means for us is that we have an opportunity to actually improve what we're doing in terms of our day to day marketing to lift what we're actually doing on regular sales volume. And we believe that we've got a test that we'd like to be able to try here to see how that works with this retailer.
Susan Tatum 17:41
So I can very much see how you're telling a story with that. Because you're not just going from point A to point C, you're you're, you're filling it in with things that are interesting, it you're just telling a story and almost getting emotionally involved.
Laura Warren 17:58
It is but it's so funny, because then because you're exactly right. Like that's exactly what we're doing. And it's getting emotionally involved. Because realistically, when we talk about business, everybody's emotionally involved in making sure that the business does what it's supposed to do. Because that's how we get paid. Right? Like we really want to be able to make sure that there's so there's an emotional element that goes in with that just to be able to get into it. It is not the emotional piece of love telling data stories. We're telling stories. We need, like a protagonist and an antagonist. And I'll know, like, yes, but no, what we really need is to connect the information to what's important. But make sure that we articulating that risk opportunity change in perspective, and tell you what you can do about it. Because that's really where we make the data live. Like we can actually make the data come to life by being able to connect to what you already thought. Or were you right or not?
Susan Tatum 18:52
Laura Warren 18:53
how does that change your perspective? And then start to highlight what were risks or opportunities? Can we now discover that that's what allows us to be able to take action or have a recommendation based on what we've learned. But it's all in that risk. It's all in making sure that we have that conversation and articulate, like have the conversation with the other person on risk, opportunity changing perspective, because that's where the value of the data really comes in.
Susan Tatum 19:17
So you said earlier in conversation that being able to to do this using data, this the storylytics, part of it is a skill not a talent.
Laura Warren 19:30
Susan Tatum 19:30
Meaning it can be taught?
Laura Warren 19:31
Susan Tatum 19:31
How do you it seems like, it seems like you could hit a few roadblocks with that.
Laura Warren 19:40
Oh, no question. Yeah. So there's, I mean, there's a few things that go into it. So I have this, I do teach an entire framework that goes against this. And I've been doing this. I've been doing what I teach now for more than 25 years. And I have formalized it in terms of this process and teaching it doing it for 25 teaching it for 20 formalize it into storylytics for eight now. So it's very much a process that we know, is validated. It's proven. It's applicable. It's practical. It's all these other elements. And the way that that the way that I teach it is to first talk about first we need to talk about audience centricity. So what do you really need to be able to understand and I provide frameworks for each one. So talent are primary skill, not talent, means that when we're actually asked these questions to in order for you to understand your audience, two or three truths, that you want to understand what your audience what's the business truth, why they're asking, please God fix this for me, you know, got this problem? That's a business truth. The personal truth is what do they think about it? What bias or opinions do they bring to the table? And if you're talking to a decision maker, they all have bias and opinion and with an experience that they're bringing to the table, they think something because they've been through before?
Susan Tatum 20:51
Laura Warren 20:52
So they always bring that to the table and knowing that that's called a personal truth. That's how you're gonna deliver an insight. So they're gonna say that it's something you did or did not know. That's a personal truth.
Susan Tatum 21:03
Laura Warren 21:04
And the final one is an influencer truth. What does that audience member have the ability of doing? So that they're actually part of the conversation in terms of where do we go next. So conversation that with a finance person is gonna be very different than the conversation you would have with a social media manager.
Susan Tatum 21:16
Laura Warren 21:17
as an example. So those three elements give you the perspective in terms of your audience, that gives you a framework to be able to say, here's, here's what the real problem I'm solving for is, then you got to go into the data. And that's the analytic process, which is separate from the storytelling process. So the analytic process, I don't I, I know I don't teach it. But the analytic processes, how do you actually know go through the data to get your answer? And then the storytelling comes in, where we start talking about, okay, now that you've actually gone all through that, then we're actually going to provide a framework that says, What's your controlling idea? What is that number one thing that somebody needs to be able understand? And then what are those elements, the points that go underneath it to support it? And then we deliver it back using something called the poet technique, which is purpose, observation, explanation and transition. And if you fill in all four of those, you've given the problem that's trying to be solved. It's easy to the end. You can you're actually, through the process, you're able to identify what is critical and relevant information on the page. Explanation says, you're going to remember to articulate risk opportunity change in perspective. And transition says, now that I know better. I've learned this, now that I know better, I can do better. What do you do next? So it's a it's a very specific, five step process, each one of which has a very clear framework that goes along with it. And basically says, If you can answer all of these questions, and you've got your probit, like it, we've got your prompting language that goes before each one. If you can fill in every single one of those, you will be a better start data storyteller you will be and then over time and practicing owning it, then it becomes far more natural.
Susan Tatum 22:58
I can see how you have a formula that you're you're following and you don't have to be particularly creative about it. You're just making sure you get the right, you consider the right things,
Laura Warren 23:12
consider the right things. Exactly. And I'm kind of listening to myself as I'm speaking. And I'm hoping it's not sounding too clinical.
Susan Tatum 23:17
No, I think it's probably comforting to a lot of people who think it's that storytelling thing that comes out of the marketing department or something.
Laura Warren 23:27
Right? Well, I do get that a lot of data scientists because a lot of data scientists, right, when you said persuasion and influence, we're not using that in the negative sense. A lot of data scientists I work for kind of like, Oh, my God, sales is lying. Yeah. No, it was pains me a little bit. I'm like, What has been your experience that you think sales is lying, because sales is not lying. But they get very concerned with telling stories, because they think that they're trying to manipulate the facts. And like, Absolutely not, you're not trying to manipulate the facts at all, we're really trying to be able to make sure that you're sharing the facts in such a way that your audience will understand data don't is you still need to stay true to the data, which was trying to be able to make sure that you're communicating in such a way that somebody else will understand.
Susan Tatum 24:08
Okay, so who you mentioned, you're working with data scientist, who are the Who Who are your most of your clients, your ideal
Laura Warren 24:15
finance and marketing actually tends to be the the primary groups that I work with. Less so on the research side, which I was find very interesting, because that's not how I went into this business. But sort of like the, in the big market, big organizations, it tends to be finance and marketing, and sometimes the consumer insight groups.
Susan Tatum 24:34
So I want to dive a little bit into you. You said that's not how you went into this business. And I think it's interesting how, and important to understand that our target markets do change as we learn about who we really are here to serve.
Laura Warren 24:50
Susan Tatum 24:50
Yours. So you started off thinking that it was going to be research people within are these larger companies.
Laura Warren 24:59
Yeah, you know, because when I started storylytics, the premise again, I'd said a lot of it was because I was talking with my clients with time like I was working corporately at the time. So if my corporate clients were like, you know, really just don't understand what all this means. And it was a smaller research shops that they were expressing some frustrations with, they didn't really understand what it meant. So I was tying it together with stuff that we were doing or if I was individually consulting. So as always, those smaller independent shops, great opportunity for them to really impact their value proposition by telling the story It stories. So that's who I thought I was really going to go work with was more of that research organization with smaller consultancies that were doing the work that that I was hearing some frustration with in terms of the executives. And that is not what happened at all. That's not who I work with today, which pains me because I do still think there's a great lot of opportunity there. So that's, that's a separate conversation. But that's where I started. But what I found was that I started to go out, I was getting calls from large organizations to be able to come in and work with our folks.
Susan Tatum 26:10
So your your focus is on working with the larger organizations, these departments within.
Laura Warren 26:19
Susan Tatum 26:20
Okay, so we're for people that are solopreneurs, or smaller consulting firms that won't be able to take advantage of your training that you do in your programs that you run. How is their book?
Laura Warren 26:40
I would love to say, yes, there's a book, but time only is so much time in a day. I see no, there's not a book. But in 2023, we will be putting more of a focus on doing more public programs. I've wanted to do this for a while and just haven't had the time. But next year, we're going to have some more structured public programs where people can come and sign up on their own. It'll be a little bit more generic, I'm going to try to keep the classes smaller so that we have more time to talk about unique situations because I work with financial service organizations, marketing, packaged goods organizations, not for profits, medical, everything in between. They all have similar yet different issues. So I want to keep the groups smaller so that we have a chance to be able to explore some of the unique situations that might show up in some of those individual industries.
Susan Tatum 27:29
Yeah, I am, I can just think of a gazillion ways that you could use what you're talking about that doesn't require a massive marketing department or something.
Laura Warren 27:40
Susan Tatum 27:40
it's just yeah, it's it's good communication. Right.
Laura Warren 27:41
That's really all it is. Yeah. So I just think and I really, you know, there's so much data and there's so much value in the data. And, and I'm such a huge proponent of it, that it just It saddens me sometimes I was actually working with a not for profit right now. And that's one of the conversations I had with them recently had been, you know, you have all the information that just saddens me that we haven't invested, we haven't been able to help you invest in actually the storytelling pieces, there's so much at your fingertips. So I've been doing some work with with those folks. And a lot of it's kind of on my own time right now. Because it just believe in some of the things that they're doing was like, let's just turn this around,
Susan Tatum 28:18
where your enthusiasm definitely comes through. Thank you so much for for spending the time with me and sharing your your ideas and your knowledge. It's very, very helpful.
Laura Warren 28:32
Susan Tatum 28:35
So for people who who do want to follow up with you, what's the best way to do that?
Laura Warren 28:37
So best way to reach out to me is through LinkedIn at Laura Warren. You can also find out through storylytics.ca And storylytics is spelled s t o r y l y t i c s.
Susan Tatum 28:50
Okay, and that's dot ca
Laura Warren 28:52
dot ca. Yeah.
Susan Tatum 28:53
which we all realize you were saying process
Laura Warren 28:58
Just forget that. Yeah. Process presentation. Just the little things, it's always
Susan Tatum 29:08
make a difference. Yeah. All right. Well, well thank you again, and have a great rest of your day.
Laura Warren 29:13
Thank you you as well.